Short description of

• problem in field (e.g. cancer)
• what is current solution (handdrawn segmentation)
• what this software does to solve it (sota segmentation)
• proposed impact (accelerated/accurate diagnosis)

git clone <thisrepo>
# build instructions

pip install mysoftware

conda install mysoftware

or using the environment

conda env create --name myproject --file=myproject.yml

sudo singularity build container/singularityrecipe.def

singularity pull repo:image.version

To run the tests ensuring the installation is valid, please run

python -m mymodule.testmycode

Which should result in

Example inference on in silico data

import seaborn as sns
import mysoftware.preprocessing as stk
import numpy as np
np.random.seed(42)
silico_data = stk.generate_insilico(args)
q = stk.infer(silico_data)
sns.boxplot(x='method', y='accuracy', data=q)

See notebooks/example.ipynb for an example interactive workflow.

See TODO for the complete API documentation

[your citation here]

See [mysoftware/insilico] on how to generate our in silico datasets. For your convenience, this can be downloaded as well:

mkdir insilico && cd insilico
wget -O insilico.hdf5 https://mydatarepo/insilico.hdf5

mkdir mydata
wget -O dataset.hdf5 https://mydatarepo/dataset.hdf5

Ensure the checksums match

md5sum dataset.hdf5

should produce

4a4f224c7b7c871855fd307ae323be93 dataset.hdf5

See scripts/preprocessing.py for the preprocessing scripts that configure the dataset and generate the plots

Please create a new issue detailing concisely, yet complete what issue you encountered, in a reproducible way.